Comparación entre K-means y redes neuronales

Abstract

Cluster analysis has been an emerging research topic in data mining due to its variety of applications. applications, it can be considered the most important unsupervised learning problem that tries to find a structure in a collection of data and that can be It can be considered the most important unsupervised learning problem that tries to find a structure in a collection of data and can be defined as the process of organizing objects into groups whose members are similar in some way. organizing objects into groups whose members are similar in some way. With the development of many data clustering algorithms and their wide use, ranging from image processing, computational biology, mobile communications, to medicine and economics, these algorithms have become very popular. have become very popular. The main problem with clustering algorithms is that they cannot be standardized. An algorithm may perform well with one type of data set, but may fail or perform poorly with other types of data. other types of data. So far, many clustering algorithms have been proposed, however, each algorithm has its own merits and demerits because they do not work well in all real situations.